Medical Physics Papers of the Week

Data-driven reconstruction has overcome similar limits in related inverse problems, but its use for ULF-MRI has been hindered by a lack of open datasets, benchmarks, and flexible simulators. To close this gap, we present OpenULF, a modular, open-source simulation toolkit that generates paired training data and supports end-to-end machine-learning (ML) reconstruction.

This work presents a new method for gradient-based optimization of the rhombic transposition flap and the excision it closes, which set the strain of the skin after closure.

We present an axisymmetric continuous simplex space-time finite element method for incompressible fluid flow.

However, it is unclear how these reconstruction algorithms reduce noise as NI changes, particularly across multiple organs. The goal of this study was to utilize an anthropomorphic phantom to evaluate image noise against the prescribed NI across different organs, determine if DLIR reduces image noise compared to ASiR-V, and use this relationship to determine the maximum volume CT dose index (CTDIvol) reduction at equivalent noise levels.

Background and purpose: We propose PGPI4MR (prior-guided, physics-informed 4D MRI reconstruction), a deep learning method that leverages information from other respiratory phases or a setup scan, the first 30 s of the same scan, to improve 4D MRI reconstruction without extra scan time.

Training them from scratch whenever a new tracer, model or protocol is used can be computationally intensive. To address this, we introduce LoRACM, a parameter-efficient framework utilizing low-rank adaptation (LoRA) to transfer a pretrained foundation CM to novel TB-PET scenarios.

This study reports the ex vivo dielectric properties of human adrenal glands, including the cortex, medulla, capsule, and tumours, based on the data obtained from four patients (diagnosed with Conn's syndrome, Cushing's syndrome, and Pheochromocytoma) who underwent unilateral adrenalectomy at the University Hospital Galway, Ireland.

This paper has developed the one-pole and two-pole Cole-Cole and Debye models for the dielectric properties of normal and diseased human trabecular bone tissue at microwave frequencies (0.5-8.5 GHz).

We developed a quantitative ultrasound framework to assess gingival perfusion and persistent inflammation.

Previous elastic analyses have demonstrated that mesh topology and skin anisotropy strongly influence graft expansion; however, the effect of progressive damage at larger deformation remains unexplored. This study therefore investigates how progressive damage affects the expansion and mechanical response of skin meshes.

In this work, we investigate a direct/indirect dual-layer detector consisting of an amorphous selenium (a-Se) direct-conversion top layer and a cesium iodide scintillator-based indirect-conversion bottom layer for enhanced visualization of small CAC.

The implementation study presented here focuses specifically on barriers to AI adoption in the diagnostic medicine workflow.

In this work, we propose a parametric source localization framework based on the Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm to estimate source positions and emitted waveforms directly from array channel data.

Quantitative image reconstruction in positron emission tomography and single photon emission computed tomography depends on how accurately the forward model describes photon emission, transport and detection.

This work develops and validates a beam model incorporating Multiple Coulomb Scattering (MCS) to estimate beam parameters.

We present a probabilistic model for photon interaction chains in a silicon detector and use it for two inference tasks at the event level: interaction order inference and classification of primary versus object-scattered photons.

Frontier language models have recently been reported to read and write the raw weights of small neural networks, an ability called weight-space programming. The purpose of this study was to determine whether such a model, given only a clinical protocol and a network's weights, can audit and repair the network.

We report the effect of two problems in our shielding items, found after the runs, and release the code, per-item outcomes and targeted-test responses.

They are regenerated for every new acquisition, field strength or relaxation rate, although identical for all of them. I propose to keep these histories instead as a replay pack, compressed into persistent, shareable tissue microphysics, so that any such query is a cheap inner product against the pack.